Institute of Bioinformatics, International Technology Park, Bangalore 560 066, Karnataka, India, Amrita School of Biotechnology, Amrita University, Kollam 690 525, Kerala, India, Centre of Excellence in Bioinformatics, School of Life Sciences, Pondicherry University, Puducherry 605 014, India, Department of Biochemistry and Molecular Biology, Pondicherry University, Puducherry 605014, India, Department of Neurochemistry, National Institute of Mental Health and Neurosciences, Bangalore 560 022, Karnataka, India, Department of Biotechnology, Kuvempu University, Shankaraghatta 577 451, Karnataka, India, Government Medical College, Bhavnagar 364 001, Gujarat, India, Mahatma Gandhi Institute of Medical Sciences, Sevagram, Wardha 442 012, Maharashtra, India, The Department of Environmental Health Sciences, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA, Department of Internal Medicine, Armed Forces Medical College, Pune 411 040, Maharashtra, India, Department of Neurology, National Institute of Mental Health and Neurosciences, Bangalore 560 022, Karnataka, India, Department of Biochemistry, La Trobe Institute for Molecular Science, La Trobe University, Melbourne, Victoria 3084, Australia, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Baltimore, MD 21205, USA, Department of Biological Chemistry, Johns Hopkins University, Baltimore, MD 21205, USA, Department of Oncology, Johns Hopkins University, Baltimore, MD 21205, USA and Department of Pathology, Johns Hopkins University, Baltimore, MD 21205, USA.
Nucleic Acids Res. 2014 Jan;42(Database issue):D959-65. doi: 10.1093/nar/gkt1251. Epub 2013 Dec 3.
Plasma Proteome Database (PPD; http://www.plasmaproteomedatabase.org/) was initially described in the year 2005 as a part of Human Proteome Organization's (HUPO's) pilot initiative on Human Plasma Proteome Project. Since then, improvements in proteomic technologies and increased throughput have led to identification of a large number of novel plasma proteins. To keep up with this increase in data, we have significantly enriched the proteomic information in PPD. This database currently contains information on 10,546 proteins detected in serum/plasma of which 3784 have been reported in two or more studies. The latest version of the database also incorporates mass spectrometry-derived data including experimentally verified proteotypic peptides used for multiple reaction monitoring assays. Other novel features include published plasma/serum concentrations for 1278 proteins along with a separate category of plasma-derived extracellular vesicle proteins. As plasma proteins have become a major thrust in the field of biomarkers, we have enabled a batch-based query designated Plasma Proteome Explorer, which will permit the users in screening a list of proteins or peptides against known plasma proteins to assess novelty of their data set. We believe that PPD will facilitate both clinical and basic research by serving as a comprehensive reference of plasma proteins in humans and accelerate biomarker discovery and translation efforts.
血浆蛋白质组数据库（PPD；http://www.plasmaproteomedatabase.org/）最初于 2005 年作为人类蛋白质组组织（HUPO）人类血浆蛋白质组项目试点计划的一部分进行了描述。自那时以来，蛋白质组学技术的改进和通量的增加导致了大量新型血浆蛋白质的鉴定。为了跟上数据的增长，我们大大丰富了 PPD 的蛋白质组学信息。该数据库目前包含了在血清/血浆中检测到的 10546 种蛋白质的信息，其中 3784 种在两项或更多研究中得到了报道。该数据库的最新版本还包含了质谱衍生的数据，包括用于多重反应监测分析的经过实验验证的蛋白质特征肽。其他新功能包括 1278 种蛋白质的已发表的血浆/血清浓度，以及一个单独的血浆衍生细胞外囊泡蛋白质类别。由于血浆蛋白质已成为生物标志物领域的主要研究方向，我们启用了一个名为 Plasma Proteome Explorer 的基于批处理的查询功能，用户可以使用该功能对已知的血浆蛋白质列表进行筛选，以评估其数据集的新颖性。我们相信，PPD 将通过成为人类血浆蛋白质的综合参考数据库，为临床和基础研究提供便利，并加速生物标志物的发现和转化工作。
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